Lifting Majority to Unanimity in Opinion Diffusion

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Author(s)
Zhuang, Zhiqiang
Wang, Kewen
Wang, Junhu
Zhang, Heng
Wang, Zhe
Gong, Zhiguo
Griffith University Author(s)
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2020
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Santiago de Compostela, Spain

Abstract

In this paper, we study an information exchange process in which a network of individuals exchanges a binary opinion. In the process, the individuals change their opinions only if a majority of their neighbours have the opposite opinion and they do it synchronously. Motivated by applications in multiagent systems, distributed computing, and social science, our goal is to derive graph-theoretic features of the network that guarantee whenever a majority of individuals initially have the same opinion, they will eventually spread the opinion to all individuals. We tackle the problem by first introducing a graph-theoretic notion called controlling set which is capable of characterising the information exchange process and, by exploiting the notion, we obtain a series of lower and upper bounds on the in-degree of vertices as well as lower bound on the size of certain neighbourhoods for guaranteeing the majority to unanimity behaviour.

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Frontiers in Artificial Intelligence and Applications

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325

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© 2020 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).

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Artificial intelligence

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Zhuang, Z; Wang, K; Wang, J; Zhang, H; Wang, Z; Gong, Z, Lifting Majority to Unanimity in Opinion Diffusion, Frontiers in Artificial Intelligence and Applications, 2020, 325, pp. 259-266